BeeGass/CS-541-Deep-Learning

CS-541 Deep Learning is a graduate class that teaches both a theoretical and practical approach to deep learning. You will be able to see this in the different homework files in the form of workable code that can be tested as well as proofs and explanations as to where the code is coming from.

34
/ 100
Emerging

This is a collection of educational materials for learning deep learning, combining theoretical explanations with practical, workable code examples. It takes complex deep learning concepts and makes them accessible through hands-on assignments. Researchers, students, or professionals looking to understand and implement deep learning models would benefit from this resource.

No commits in the last 6 months.

Use this if you are a graduate student or professional seeking to learn deep learning with a balance of theoretical understanding and practical coding exercises.

Not ideal if you are looking for a plug-and-play deep learning library for immediate application without delving into the underlying principles.

deep-learning-education machine-learning-training neural-networks-study data-science-learning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

10

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 31, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/BeeGass/CS-541-Deep-Learning"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.